Area sampling for rapid population assessment

In the initial phase of an emergency, an immediate assessment of population size is vital to provide relief workers with the necessary data to plan relief activities. While a head count (census) leading to a registration is the ideal method of obtaining information on population size and composition, such an exercise can often be extremely difficult to implement especially in the early stages of a large complex emergency. It is now accepted that as preparations for a census are underway, other strategies may be necessary in order to rapidly estimate numbers2. There are several approaches that can be used; mass screening of all children under five years of age, counting females above 118 cms, aerial photography, vaccination campaigns including information on coverage and using Satellite Geographic Systems GPS. All these methods have advantages and disadvantages which must be considered on a case by case basis. In the past decade an approach based on area sampling in camps has been developed and improved. There are two stages. The first is to map the camp by registering all of its coordinates. In the second stage the total camp population is estimated by counting the population living in a limited number of square blocks of known surface area and by extrapolating average population calculated per block to the total camp surface.

A recent study has examined data from six refugee camps in Africa and Asia (between 1992-94), where populations were rapidly estimated within the first one to two days of arrival using an area sampling methodology. After measuring all external limits, surface areas were calculated and ranged between 1,213,000 and 2,770,000 square metres. In five camps, the average population per square block was obtained using blocks measuring 25 by 25 metres and for another camp with blocks 100 by 100 square metres. In three camps, different population density zones were defined. The principal aims of the study were to determine whether population estimates could be obtained rapidly using the method and to identify methodological strengths and weaknesses.

The study concluded that the area sampling method was efficient in providing population estimates within one or two days. The validity of the method could however only be fully evaluated in Liboi camp for Somali refugees (in Kenya) where a population census conducted a few weeks after the assessment estimated the camp population at 45,000 refugees as compared to the 43,000 figure obtained through the area sampling method.

The study also found limitations with the sampling method. For example, there are issues related to selection of the population density zones and to the number of square blocks needed. Stratification3 per density zone is mainly used as a way to enhance precision. Ideally, a single population density zone could be considered if the sample was made up of a sufficient number of square blocks (breaking up the camp in smaller, countable areas). However, the number of square blocks sampled varied between different camp experiences and was driven by working conditions and logistical constraints.

The question of selecting the most adequate number and size of square blocks remained unanswered in the study and merits further research for the method to be better validated. Number of blocks ranged from five to 26 and the dimensions varied from 25-100 square metres. Statistical principles suggest that the higher the number of square blocks selected the more accurate the samples representativeness and that selecting a higher number of small blocks would be better than relying on fewer big blocks. The authors of the study concluded that the statistical validity of rapid population estimates should be tested by comparing results to those of an exhaustive population count carried out simultaneously. Furthermore, alternative area sampling methods such as the 'T-square' method'4 might also be considered according to the study authors. Such methods have been used in agronomy and rely on the calculation of the average occupancy area of a unit. As the measurement of only 50 points selected at random are necessary, the method could be faster to implement and thus useful in situations with limited resources. However, the method may be limited by heterogeneity of population distribution. This method also therefore needs further testing and validation.

2UNHCR (1995): Report of a Workshop on Tools and Strategies in Needs Assessment and the Management of Food and Nutrition Programmes in Refugee and Displaced Populations. Addis Ababa, Ethiopia, 15-21st October 1995.

3Stratifying implies the division of the target population into distinct sub-groups or 'layers' i.e. strata, in this case division of the population into sub-groups is based on the density of the population in that 'block'.